2.4 KiB
(fastvideo-installation)=
🔧 Installation
FastVideo currently only supports Linux and NVIDIA CUDA GPUs.
Requirements
- OS: Linux
- Python: 3.10-3.12
- CUDA 12.4
- At least 1 NVIDIA GPU
Quick start
We recommend using an environment manager such as Conda
pip install fastvideo
Also optionally install flash-attn:
pip install flash-attn==2.7.4.post1 --no-build-isolation
Click here to install from source
Environment Setup
We highly recommend using a conda or virtualenv environment:
Miniconda (Recommended)
1. Install Miniconda (if not already installed)
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
source ~/.bashrc
2. Create and activate a Conda environment for FastVideo
conda create -n fastvideo python=3.10 -y
conda activate fastvideo
Installation from Source
1. Clone the FastVideo repository
git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo
2. Install FastVideo
Basic installation:
pip install -e .
Optional Dependencies
Flash Attention
pip install flash-attn==2.7.4.post1 --no-build-isolation
Sliding Tile Attention (STA) (Requires CUDA 12.4 and H100)
To try Sliding Tile Attention (optional), please follow the instructions in csrc/sliding_tile_attention/README.md to install STA.
Docker Images
We also have prebuilt docker images with FastVideo dependencies pre-installed: Docker Images
Development Environment Setup
If you're planning to contribute to FastVideo please see the following page: Contributor Guide
Hardware Requirements
For Basic Inference
- NVIDIA GPU with CUDA 12.4support
For Lora Finetuning
- 40GB GPU memory each for 2 GPUs with lora
- 30GB GPU memory each for 2 GPUs with CPU offload and lora
For Full Finetuning/Distillation
- Multiple high-memory GPUs recommended (e.g., H100)
Troubleshooting
If you encounter any issues during installation, please open an issue on our GitHub repository.
You can also join our Slack community for additional support.